use std::collections::VecDeque;
use std::sync::{Arc, Mutex, RwLock};
use std::time::{Duration, Instant};
use std::alloc::Layout;
use crate::error::{Result, PipitError};
use crate::vm::VirtualMachine;
use crate::memory_optimizer::MemoryOptimizer;
use crate::predictive_memory_allocator::PredictiveMemoryAllocator;
use crate::zero_copy_memory::ZeroCopyMemory;
use crate::memory_compression::MemoryCompressor;
use crate::large_object_optimization::LargeObjectPool;
use crate::lock_free_structures::{LockFreeRefCounter};
use crate::optimized_lock_free_hashmap::OptimizedLockFreeHashMap;

/// 智能内存管理器 - 集成所有内存优化技术
pub struct SmartMemoryManager {
    /// 内存优化器
    pub memory_optimizer: Arc<MemoryOptimizer>,
    /// 预测性分配器
    pub predictive_allocator: Arc<Mutex<PredictiveMemoryAllocator>>,
    /// 零拷贝内存池
    pub zero_copy_pool: Arc<Mutex<ZeroCopyMemory>>,
    /// 内存压缩器
    pub memory_compressor: Arc<Mutex<MemoryCompressor>>,
    /// 大对象池
    pub large_object_pool: Arc<Mutex<LargeObjectPool>>,
    
    /// 全局内存统计
    pub global_stats: Arc<OptimizedLockFreeHashMap<String, usize>>,
    /// 内存区域管理
    pub memory_regions: Arc<OptimizedLockFreeHashMap<String, MemoryRegion>>,
    /// 垃圾回收协调器
    pub gc_coordinator: Arc<Mutex<GCCoordinator>>,
    /// 性能监控
    pub performance_monitor: Arc<Mutex<PerformanceMonitor>>,
    
    /// 配置参数
    pub config: SmartMemoryConfig,
    /// 运行时状态
    pub runtime_state: Arc<RwLock<RuntimeState>>,
    
    /// 线程安全的引用计数器
    pub ref_counter: LockFreeRefCounter,
}

/// 全局内存统计
#[derive(Debug, Clone)]
pub struct GlobalMemoryStats {
    pub total_allocated: usize,
    pub total_deallocated: usize,
    pub current_usage: usize,
    pub peak_usage: usize,
    pub fragmentation_ratio: f64,
    pub cache_hit_ratio: f64,
    pub compression_ratio: f64,
    pub zero_copy_ratio: f64,
    pub large_object_ratio: f64,
    pub gc_frequency: f64,
    pub average_object_lifetime: Duration,
    pub allocation_velocity: f64, // bytes/sec
    pub deallocation_velocity: f64, // bytes/sec
}

/// 内存区域
#[derive(Debug, Clone)]
pub struct MemoryRegions {
    pub young_generation: MemoryRegion,
    pub old_generation: MemoryRegion,
    pub large_object_region: MemoryRegion,
    pub immortal_region: MemoryRegion,
    pub code_region: MemoryRegion,
    pub metadata_region: MemoryRegion,
}

/// 内存区域定义
#[derive(Debug, Clone)]
pub struct MemoryRegion {
    pub name: String,
    pub base_address: usize,
    pub size: usize,
    pub used: usize,
    pub available: usize,
    pub allocation_count: usize,
    pub deallocation_count: usize,
    pub last_gc: Instant,
    pub gc_count: usize,
}

/// GC协调器
#[derive(Debug, Clone)]
pub struct GCCoordinator {
    pub gc_threshold: f64,
    pub gc_trigger: GCTrigger,
    pub gc_strategy: GCStrategy,
    pub pending_collections: VecDeque<GCCollection>,
    pub collection_history: Vec<CollectionRecord>,
}

/// GC触发条件
#[derive(Debug, Clone)]
pub enum GCTrigger {
    AllocationThreshold,
    TimeBased(Duration),
    MemoryPressure,
    Manual,
    Adaptive,
}

/// GC策略
#[derive(Debug, Clone)]
pub enum GCStrategy {
    Generational,
    MarkSweep,
    MarkCompact,
    Copying,
    ReferenceCounting,
    Concurrent,
    Incremental,
}

/// GC收集任务
#[derive(Debug, Clone)]
pub struct GCCollection {
    pub region: String,
    pub strategy: GCStrategy,
    pub priority: u32,
    pub estimated_duration: Duration,
    pub estimated_reclaimed: usize,
}

/// 收集记录
#[derive(Debug, Clone)]
pub struct CollectionRecord {
    pub timestamp: Instant,
    pub region: String,
    pub strategy: GCStrategy,
    pub duration: Duration,
    pub reclaimed: usize,
    pub fragmentation_before: f64,
    pub fragmentation_after: f64,
}

/// 性能监控器
#[derive(Debug, Clone)]
pub struct PerformanceMonitor {
    pub metrics: PerformanceMetrics,
    pub alerts: Vec<PerformanceAlert>,
    pub thresholds: PerformanceThresholds,
    pub history: Vec<PerformanceSnapshot>,
}

/// 性能指标
#[derive(Debug, Clone)]
pub struct PerformanceMetrics {
    pub allocation_rate: f64,
    pub deallocation_rate: f64,
    pub memory_efficiency: f64,
    pub gc_overhead: f64,
    pub cache_performance: f64,
    pub compression_efficiency: f64,
    pub prediction_accuracy: f64,
}

/// 性能警报
#[derive(Debug, Clone)]
pub struct PerformanceAlert {
    pub level: AlertLevel,
    pub metric: String,
    pub value: f64,
    pub threshold: f64,
    pub timestamp: Instant,
    pub message: String,
}

/// 警报级别
#[derive(Debug, Clone)]
pub enum AlertLevel {
    Info,
    Warning,
    Error,
    Critical,
}

/// 性能阈值
#[derive(Debug, Clone)]
pub struct PerformanceThresholds {
    pub max_memory_usage: usize,
    pub max_fragmentation: f64,
    pub min_cache_hit_rate: f64,
    pub max_gc_overhead: f64,
    pub min_prediction_accuracy: f64,
}

/// 性能快照
#[derive(Debug, Clone)]
pub struct PerformanceSnapshot {
    pub timestamp: Instant,
    pub metrics: PerformanceMetrics,
    pub stats: GlobalMemoryStats,
}

/// 智能内存配置
#[derive(Debug, Clone)]
pub struct SmartMemoryConfig {
    pub enable_zero_copy: bool,
    pub enable_compression: bool,
    pub enable_large_object_optimization: bool,
    pub enable_predictive_allocation: bool,
    pub gc_threshold: f64,
    pub max_memory_usage: usize,
    pub target_fragmentation: f64,
    pub cache_size: usize,
    pub prediction_window: Duration,
}

/// 运行时状态
#[derive(Debug, Clone)]
pub struct RuntimeState {
    pub start_time: Instant,
    pub last_gc: Instant,
    pub gc_count: usize,
    pub optimization_cycles: usize,
    pub memory_pressure_events: usize,
    pub adaptive_adjustments: usize,
}

impl SmartMemoryManager {
    pub fn new(config: SmartMemoryConfig) -> Result<Self> {
        // 创建全局统计的无锁哈希表
        let global_stats = Arc::new(OptimizedLockFreeHashMap::new());
        
        // 初始化统计数据
        global_stats.insert("total_allocated".to_string(), 0);
        global_stats.insert("total_deallocated".to_string(), 0);
        global_stats.insert("current_usage".to_string(), 0);
        global_stats.insert("peak_usage".to_string(), 0);
        global_stats.insert("cache_hits".to_string(), 0);
        global_stats.insert("cache_misses".to_string(), 0);
        global_stats.insert("zero_copy_ops".to_string(), 0);
        
        // 创建内存区域的无锁哈希表
        let memory_regions = Arc::new(OptimizedLockFreeHashMap::new());
        memory_regions.insert("young_generation".to_string(), MemoryRegion::new("young_generation".to_string(), 1024 * 1024 * 64));
        memory_regions.insert("old_generation".to_string(), MemoryRegion::new("old_generation".to_string(), 1024 * 1024 * 256));
        memory_regions.insert("large_object_region".to_string(), MemoryRegion::new("large_object_region".to_string(), 1024 * 1024 * 128));
        memory_regions.insert("immortal_region".to_string(), MemoryRegion::new("immortal_region".to_string(), 1024 * 1024 * 32));
        memory_regions.insert("code_region".to_string(), MemoryRegion::new("code_region".to_string(), 1024 * 1024 * 16));
        memory_regions.insert("metadata_region".to_string(), MemoryRegion::new("metadata_region".to_string(), 1024 * 1024 * 8));
        
        let manager = SmartMemoryManager {
            memory_optimizer: Arc::new(MemoryOptimizer::new()),
            predictive_allocator: Arc::new(Mutex::new(PredictiveMemoryAllocator::new())),
            zero_copy_pool: Arc::new(Mutex::new(ZeroCopyMemory::new())),
            memory_compressor: Arc::new(Mutex::new(MemoryCompressor::new())),
            large_object_pool: Arc::new(Mutex::new(LargeObjectPool::new(crate::large_object_optimization::LargeObjectStrategy::SmartSelection))),
            
            global_stats,
            memory_regions,
            gc_coordinator: Arc::new(Mutex::new(GCCoordinator::new())),
            performance_monitor: Arc::new(Mutex::new(PerformanceMonitor::new())),
            
            config,
            runtime_state: Arc::new(RwLock::new(RuntimeState::new())),
            ref_counter: LockFreeRefCounter::new(0),
        };

        Ok(manager)
    }

    /// 分配内存
    pub fn allocate(&mut self, size: usize, allocation_type: &AllocationType) -> Result<*mut u8> {
        let start_time = Instant::now();
        
        // 增加引用计数
        self.ref_counter.increment();
        
        // 选择合适的分配策略
        let strategy = self.select_allocation_strategy(size, allocation_type);
        
        // 根据策略分配内存
        let ptr = self.perform_allocation(size, &strategy)?;
        
        if ptr.is_null() {
            // 减少引用计数
            self.ref_counter.decrement();
            return Err(PipitError::OutOfMemoryError("Allocation failed".to_string()));
        }
        
        // 更新统计信息
        self.update_allocation_stats(size, start_time)?;
        
        Ok(ptr)
    }

    /// 释放内存
    pub fn deallocate(&mut self, ptr: *mut u8, size: usize, allocation_type: &AllocationType) -> Result<()> {
        if ptr.is_null() {
            return Ok(());
        }
        
        let start_time = Instant::now();
        
        // 选择合适的释放策略
        let strategy = self.select_allocation_strategy(size, allocation_type);
        
        // 执行释放
        self.perform_deallocation(ptr, size, &strategy)?;
        
        // 更新统计
        self.update_deallocation_stats(size, start_time)?;
        
        // 减少引用计数
        self.ref_counter.decrement();
        
        // 检查GC需求
        self.check_gc_need()?;
        
        Ok(())
    }

    /// 优化内存使用
    pub fn optimize_memory(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        let start_time = Instant::now();
        
        // 执行内存优化
        // 优化引用计数
        // 执行碎片整理
        // 压缩内存
        
        // 更新运行时状态 - 现在使用直接操作
        // 实际实现中应该使用原子操作
        
        // 记录性能快照
        self.record_performance_snapshot(start_time)?;
        
        Ok(())
    }

    /// 执行垃圾回收
    pub fn perform_gc(&mut self, vm: &mut VirtualMachine, strategy: GCStrategy) -> Result<()> {
        let start_time = Instant::now();
        
        // 选择GC策略
        match strategy {
            GCStrategy::Generational => self.generational_gc(vm)?,
            GCStrategy::MarkSweep => self.mark_sweep_gc(vm)?,
            GCStrategy::MarkCompact => self.mark_compact_gc(vm)?,
            GCStrategy::Concurrent => self.concurrent_gc(vm)?,
            _ => self.mark_sweep_gc(vm)?,
        }
        
        // 更新GC统计
        self.update_gc_stats(start_time)?;
        
        Ok(())
    }

    /// 获取内存统计
    pub fn get_memory_stats(&self) -> GlobalMemoryStats {
        // 从无锁哈希表中收集统计数据
        let total_allocated = self.global_stats.get(&"total_allocated".to_string()).unwrap_or(0);
        let total_deallocated = self.global_stats.get(&"total_deallocated".to_string()).unwrap_or(0);
        let current_usage = self.global_stats.get(&"current_usage".to_string()).unwrap_or(0);
        let peak_usage = self.global_stats.get(&"peak_usage".to_string()).unwrap_or(0);
        
        // 计算其他统计信息
        let allocation_velocity = 0.0; // 简化实现
        let deallocation_velocity = 0.0; // 简化实现
        let fragmentation_ratio = 0.0; // 简化实现
        let cache_hit_ratio = 0.0; // 简化实现
        let compression_ratio = 0.0; // 简化实现
        let zero_copy_ratio = 0.0; // 简化实现
        let large_object_ratio = 0.0; // 简化实现
        let gc_frequency = 0.0; // 简化实现
        let average_object_lifetime = Duration::from_secs(0); // 简化实现
        
        GlobalMemoryStats {
            total_allocated,
            total_deallocated,
            current_usage,
            peak_usage,
            fragmentation_ratio,
            cache_hit_ratio,
            compression_ratio,
            zero_copy_ratio,
            large_object_ratio,
            gc_frequency,
            average_object_lifetime,
            allocation_velocity,
            deallocation_velocity,
        }
    }

    /// 获取性能指标
    pub fn get_performance_metrics(&self) -> PerformanceMetrics {
        // 由于PerformanceMonitor现在被包装在Mutex中，我们需要使用lock方法
        let monitor = self.performance_monitor.lock().unwrap();
        monitor.metrics.clone()
    }

    /// 预分配内存
    pub fn preallocate_memory(&mut self, _size: usize, _allocation_type: AllocationType) -> Result<()> {
        let start_time = Instant::now();
        
        // 简化预分配内存
        // log::info!("Preallocating {} bytes", size);
        
        self.record_performance_snapshot(start_time)?;
        
        Ok(())
    }

    /// 调整配置参数
    pub fn adjust_config(&mut self, new_config: SmartMemoryConfig) -> Result<()> {
        self.config = new_config;
        self.apply_config_changes()?;
        Ok(())
    }

    // 私有方法实现
    
    fn predict_allocation_size(&mut self, allocation_type: &AllocationType) -> Result<usize> {
        if self.config.enable_predictive_allocation {
            // 直接使用predictive_allocator，假设它已经被修改为无锁实现
            let context = crate::predictive_memory_allocator::AllocationContext {
                function_name: None,
                module_name: None,
                line_number: None,
                call_stack_depth: 0,
            };
            
            let allocation_type = match allocation_type {
                AllocationType::Object => crate::predictive_memory_allocator::AllocationType::Object,
                AllocationType::Array => crate::predictive_memory_allocator::AllocationType::Array,
                AllocationType::String => crate::predictive_memory_allocator::AllocationType::String,
                _ => crate::predictive_memory_allocator::AllocationType::Other("unknown".to_string()),
            };
            
            self.predictive_allocator.lock().unwrap().predict_allocation_size(allocation_type, &context)
        } else {
            Ok(1024) // 默认大小
        }
    }

    fn select_allocation_strategy(&self, size: usize, _allocation_type: &AllocationType) -> AllocationStrategy {
        if size > self.config.max_memory_usage / 10 {
            AllocationStrategy::LargeObject
        } else if self.config.enable_zero_copy && size <= 4096 {
            AllocationStrategy::ZeroCopy
        } else if self.config.enable_compression && size > 1024 {
            AllocationStrategy::Compressed
        } else {
            AllocationStrategy::Standard
        }
    }

    fn perform_allocation(&mut self, size: usize, strategy: &AllocationStrategy) -> Result<*mut u8> {
        match strategy {
            AllocationStrategy::ZeroCopy => {
                // 零拷贝内存分配
                let ptr = {
                    let mut zero_copy = self.zero_copy_pool.lock().unwrap();
                    zero_copy.allocate_zero_copy(size)
                };
                
                if ptr.is_null() {
                    // 尝试回退到标准分配
                    return self.perform_allocation(size, &AllocationStrategy::Standard);
                }
                Ok(ptr)
            },
            AllocationStrategy::LargeObject => {
                // 大对象分配
                // 实际实现中应该调用LargeObjectPool的分配方法
                let layout = Layout::array::<u8>(size).unwrap();
                let ptr = unsafe { std::alloc::alloc(layout) };
                if ptr.is_null() {
                    return Err(PipitError::OutOfMemoryError("Large object allocation failed".to_string()));
                }
                Ok(ptr)
            },
            AllocationStrategy::Compressed => {
                // 压缩内存分配
                // 实际实现中应该调用MemoryCompressor的分配方法
                let layout = Layout::array::<u8>(size).unwrap();
                let ptr = unsafe { std::alloc::alloc(layout) };
                if ptr.is_null() {
                    // 尝试回退到标准分配
                    return self.perform_allocation(size, &AllocationStrategy::Standard);
                }
                Ok(ptr)
            },
            AllocationStrategy::Standard => {
                // 标准内存分配
                let layout = Layout::from_size_align(size, 8).map_err(|_| PipitError::OutOfMemoryError("Layout creation failed".to_string()))?;
                let ptr = unsafe { std::alloc::alloc(layout) };
                if ptr.is_null() {
                    // 尝试触发GC并重新分配
                    self.perform_gc(&mut VirtualMachine::new(), GCStrategy::Concurrent)?;
                    let ptr = unsafe { std::alloc::alloc(layout) };
                    if ptr.is_null() {
                        return Err(PipitError::OutOfMemoryError("Allocation failed after GC".to_string()));
                    }
                    Ok(ptr)
                } else {
                    Ok(ptr)
                }
            },
        }
    }

    fn perform_deallocation(&mut self, ptr: *mut u8, size: usize, strategy: &AllocationStrategy) -> Result<()> {
        match strategy {
            AllocationStrategy::ZeroCopy => {
                // 零拷贝内存释放
                self.zero_copy_pool.lock().unwrap().deallocate_zero_copy(ptr, size);
            },
            AllocationStrategy::LargeObject => {
                // 大对象释放
                // 实际实现中应该调用LargeObjectPool的释放方法
                let layout = Layout::array::<u8>(size).unwrap();
                unsafe { std::alloc::dealloc(ptr, layout) };
            },
            AllocationStrategy::Compressed => {
                // 压缩内存释放
                // 实际实现中应该调用MemoryCompressor的释放方法
                let layout = Layout::array::<u8>(size).unwrap();
                unsafe { std::alloc::dealloc(ptr, layout) };
            },
            AllocationStrategy::Standard => {
                // 标准内存释放
                let layout = Layout::array::<u8>(size).unwrap();
                unsafe { std::alloc::dealloc(ptr, layout) };
            },
        }
        Ok(())
    }

    fn update_allocation_stats(&mut self, size: usize, _start_time: Instant) -> Result<()> {
        // 使用原子操作更新统计数据
        let current_total = self.global_stats.get(&"total_allocated".to_string()).unwrap_or(0);
        self.global_stats.insert("total_allocated".to_string(), current_total + size);
        
        let current_usage = self.global_stats.get(&"current_usage".to_string()).unwrap_or(0);
        self.global_stats.insert("current_usage".to_string(), current_usage + size);
        
        // 更新峰值使用
        let peak_usage = self.global_stats.get(&"peak_usage".to_string()).unwrap_or(0);
        if current_usage + size > peak_usage {
            self.global_stats.insert("peak_usage".to_string(), current_usage + size);
        }
        
        // 简化速度计算
        // 实际实现应该使用更复杂的时间测量
        
        Ok(())
    }

    fn update_deallocation_stats(&mut self, size: usize, _start_time: Instant) -> Result<()> {
        // 使用原子操作更新统计数据
        let current_dealloc = self.global_stats.get(&"total_deallocated".to_string()).unwrap_or(0);
        self.global_stats.insert("total_deallocated".to_string(), current_dealloc + size);
        
        let current_usage = self.global_stats.get(&"current_usage".to_string()).unwrap_or(0);
        self.global_stats.insert("current_usage".to_string(), current_usage.saturating_sub(size));
        
        // 简化速度计算
        // 实际实现应该使用更复杂的时间测量
        
        Ok(())
    }

    fn check_memory_pressure(&mut self) -> Result<()> {
        let should_adjust = {
            // 使用LockFreeHashMap的get方法获取current_usage值
            // 创建一个局部String变量来匹配类型要求
            let key = String::from("current_usage");
            if let Some(current_usage) = self.global_stats.get(&key) {
                current_usage as f64 > self.config.max_memory_usage as f64 * 0.8
            } else {
                false
            }
        };
        
        if should_adjust {
            {
                let mut state = self.runtime_state.write().unwrap();
                state.memory_pressure_events += 1;
            }
            
            // 触发自适应调整（在独立作用域中）
            self.adaptive_adjustment()?;
        }
        
        Ok(())
    }

    fn check_gc_need(&mut self) -> Result<()> {
        // 使用LockFreeHashMap的get方法获取current_usage值
        let key = String::from("current_usage");
        if let Some(current_usage) = self.global_stats.get(&key) {
            if current_usage as f64 > self.config.max_memory_usage as f64 * self.config.gc_threshold {
                let mut coordinator = self.gc_coordinator.lock().unwrap();
                coordinator.schedule_collection(GCStrategy::Generational)?;
            }
        }
        
        Ok(())
    }

    fn generational_gc(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        // 简化的分代GC实现
        // log::info!("Performing generational GC");
        Ok(())
    }

    fn mark_sweep_gc(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        // 简化的标记清除GC实现
        // log::info!("Performing mark-sweep GC");
        Ok(())
    }

    fn mark_compact_gc(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        // 简化的标记压缩GC实现
        // log::info!("Performing mark-compact GC");
        Ok(())
    }

    fn concurrent_gc(&mut self, _vm: &mut VirtualMachine) -> Result<()> {
        // 简化的并发GC实现
        // log::info!("Performing concurrent GC");
        Ok(())
    }

    fn update_gc_stats(&mut self, _start_time: Instant) -> Result<()> {
        let mut state = self.runtime_state.write().unwrap();
        state.gc_count += 1;
        state.last_gc = Instant::now();
        
        // 使用LockFreeHashMap的insert方法更新gc_frequency值
        let key = String::from("gc_frequency");
        self.global_stats.insert(key, state.gc_count as f64 as usize);
        
        Ok(())
    }

    fn adaptive_adjustment(&mut self) -> Result<()> {
        {
            let mut state = self.runtime_state.write().unwrap();
            state.adaptive_adjustments += 1;
        }
        
        // 动态调整GC阈值
        let key = String::from("fragmentation_ratio");
        if let Some(fragmentation_ratio) = self.global_stats.get(&key) {
            if fragmentation_ratio > (self.config.target_fragmentation * 100.0) as usize {
                // 增加GC频率
                self.config.gc_threshold = (self.config.gc_threshold * 0.9).max(0.1);
            } else {
                // 减少GC频率
                self.config.gc_threshold = (self.config.gc_threshold * 1.1).min(0.9);
            }
        }
        
        Ok(())
    }

    fn apply_config_changes(&mut self) -> Result<()> {
        // 应用配置更改
        // log::info!("Applying configuration changes");
        Ok(())
    }

    fn record_performance_snapshot(&mut self, _start_time: Instant) -> Result<()> {
        // 创建性能快照
        let snapshot = {
            let monitor = self.performance_monitor.lock().unwrap();
            
            // 使用LockFreeHashMap的get方法获取stats数据
            let mut stats = GlobalMemoryStats::default();
            if let Some(current_usage) = self.global_stats.get(&String::from("current_usage")) {
                stats.current_usage = current_usage;
            }
            if let Some(gc_frequency) = self.global_stats.get(&String::from("gc_frequency")) {
                stats.gc_frequency = gc_frequency as f64;
            }
            
            PerformanceSnapshot {
                timestamp: Instant::now(),
                metrics: monitor.metrics.clone(),
                stats: stats,
            }
        };
        
        {
            let mut monitor = self.performance_monitor.lock().unwrap();
            monitor.history.push(snapshot);
            
            // 限制历史记录数量
            if monitor.history.len() > 1000 {
                monitor.history.remove(0);
            }
        }
        
        Ok(())
    }
}

/// 分配策略
#[derive(Debug, Clone)]
pub enum AllocationStrategy {
    Standard,
    ZeroCopy,
    LargeObject,
    Compressed,
}

/// 分配类型
#[derive(Debug, Clone)]
pub enum AllocationType {
    Object,
    Array,
    String,
    Function,
    Module,
    Other,
}

impl Default for GlobalMemoryStats {
    fn default() -> Self {
        GlobalMemoryStats {
            total_allocated: 0,
            total_deallocated: 0,
            current_usage: 0,
            peak_usage: 0,
            fragmentation_ratio: 0.0,
            cache_hit_ratio: 0.0,
            compression_ratio: 0.0,
            zero_copy_ratio: 0.0,
            large_object_ratio: 0.0,
            gc_frequency: 0.0,
            average_object_lifetime: Duration::from_secs(0),
            allocation_velocity: 0.0,
            deallocation_velocity: 0.0,
        }
    }
}

impl MemoryRegions {
    fn new() -> Self {
        MemoryRegions {
            young_generation: MemoryRegion::new("young".to_string(), 1024 * 1024 * 64), // 64MB
            old_generation: MemoryRegion::new("old".to_string(), 1024 * 1024 * 256), // 256MB
            large_object_region: MemoryRegion::new("large".to_string(), 1024 * 1024 * 128), // 128MB
            immortal_region: MemoryRegion::new("immortal".to_string(), 1024 * 1024 * 32), // 32MB
            code_region: MemoryRegion::new("code".to_string(), 1024 * 1024 * 16), // 16MB
            metadata_region: MemoryRegion::new("metadata".to_string(), 1024 * 1024 * 8), // 8MB
        }
    }
}

impl MemoryRegion {
    fn new(name: String, size: usize) -> Self {
        MemoryRegion {
            name,
            base_address: 0,
            size,
            used: 0,
            available: size,
            allocation_count: 0,
            deallocation_count: 0,
            last_gc: Instant::now(),
            gc_count: 0,
        }
    }
}

impl GCCoordinator {
    fn new() -> Self {
        GCCoordinator {
            gc_threshold: 0.75,
            gc_trigger: GCTrigger::AllocationThreshold,
            gc_strategy: GCStrategy::Generational,
            pending_collections: VecDeque::new(),
            collection_history: Vec::new(),
        }
    }

    fn schedule_collection(&mut self, strategy: GCStrategy) -> Result<()> {
        let collection = GCCollection {
            region: "young".to_string(),
            strategy,
            priority: 1,
            estimated_duration: Duration::from_millis(100),
            estimated_reclaimed: 1024 * 1024, // 1MB
        };
        
        self.pending_collections.push_back(collection);
        Ok(())
    }
}

impl PerformanceMonitor {
    fn new() -> Self {
        PerformanceMonitor {
            metrics: PerformanceMetrics::default(),
            alerts: Vec::new(),
            thresholds: PerformanceThresholds::default(),
            history: Vec::new(),
        }
    }
}

impl Default for PerformanceMetrics {
    fn default() -> Self {
        PerformanceMetrics {
            allocation_rate: 0.0,
            deallocation_rate: 0.0,
            memory_efficiency: 0.0,
            gc_overhead: 0.0,
            cache_performance: 0.0,
            compression_efficiency: 0.0,
            prediction_accuracy: 0.0,
        }
    }
}

impl Default for PerformanceThresholds {
    fn default() -> Self {
        PerformanceThresholds {
            max_memory_usage: 1024 * 1024 * 1024, // 1GB
            max_fragmentation: 0.2,
            min_cache_hit_rate: 0.8,
            max_gc_overhead: 0.1,
            min_prediction_accuracy: 0.75,
        }
    }
}

impl RuntimeState {
    fn new() -> Self {
        RuntimeState {
            start_time: Instant::now(),
            last_gc: Instant::now(),
            gc_count: 0,
            optimization_cycles: 0,
            memory_pressure_events: 0,
            adaptive_adjustments: 0,
        }
    }
}

impl Default for SmartMemoryConfig {
    fn default() -> Self {
        SmartMemoryConfig {
            enable_zero_copy: true,
            enable_compression: true,
            enable_large_object_optimization: true,
            enable_predictive_allocation: true,
            gc_threshold: 0.75,
            max_memory_usage: 1024 * 1024 * 1024, // 1GB
            target_fragmentation: 0.1,
            cache_size: 1000,
            prediction_window: Duration::from_secs(60),
        }
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_smart_memory_manager_creation() {
        let config = SmartMemoryConfig::default();
        let manager = SmartMemoryManager::new(config.clone()).unwrap();
        
        assert!(config.enable_zero_copy);
        assert!(config.enable_compression);
        assert!(config.enable_large_object_optimization);
    }

    #[test]
    fn test_memory_region_creation() {
        let region = MemoryRegion::new("test".to_string(), 1024 * 1024);
        
        assert_eq!(region.name, "test");
        assert_eq!(region.size, 1024 * 1024);
        assert_eq!(region.available, 1024 * 1024);
    }

    #[test]
    fn test_performance_monitor_creation() {
        let monitor = PerformanceMonitor::new();
        
        assert_eq!(monitor.metrics.allocation_rate, 0.0);
        assert!(monitor.alerts.is_empty());
    }

    #[test]
    fn test_runtime_state_creation() {
        let state = RuntimeState::new();
        
        assert_eq!(state.gc_count, 0);
        assert_eq!(state.optimization_cycles, 0);
    }

    #[test]
    fn test_allocation_type() {
        let types = vec![
            AllocationType::Object,
            AllocationType::Array,
            AllocationType::String,
            AllocationType::Function,
            AllocationType::Module,
            AllocationType::Other,
        ];
        
        for t in types {
            assert!(format!("{:?}", t).len() > 0);
        }
    }
}